Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Exercise;Use social media;Watch sports;Attend football matches 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Digital content creation (e.g., creation of social media content);Solving math or logical problems;Brainstorming;Learning (e.g., explaining complex concepts in simple terms);Summarizing long texts 
Contexts of LLM use: Work;School/University;Personal;Learning;Creative or artistic 
Prompt 1: shorten this to a single paragraph
Prompt 2: recall a situation in which you shared a personal failure with someone at work and describe that failure to us
Prompt 3: do you know about the fiit model?
Prompt 4: I am good. I have a few questions about climate change
Prompt 5: rewrite the post in less than 280 characters
Prompt 6: add some hashtags
Prompt 7: I want to start a business. Problem is I don't have the slightest clue how to go about it.  I have an idea though. I want to sell vape products. vape pens, bongs, rolling paper, that kind of stuff
Prompt 8: Can you create an image of my pet? I'd love to have a fun and creative representation.
Prompt 9: a brown and black German shepherd male. very gentle, playful and friendly
Prompt 10: Please think of one reason explaining why you think you will NOT buy this product. Write that reason succinctly in one sentence.
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